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#include <stdio.h>
#include <stdlib.h>
#include <string.h>
void IShouldNeverBeCalled() {
puts("I should never be called");
exit(0);
}
void vulnerable(char *arg) {
import json
class PostDetais(object):
def __init__(self, soup, link=None):
self.page_soup = soup
self.link = link
def get_title(self):
class_names = ['graf graf--h3 graf-after--figure graf--title',
// Function Pointer
#include <stdio.h>
int sum(int a, int b)
{
return a+b;
}
void hello_name(char *name)
// source: https://stackoverflow.com/questions/43849847/executing-shellcode-in-shared-memory-with-mmap
#include <string.h>
#include <sys/mman.h>
// /bin/sh shellcode
const char shellcode[] = "\x01\x30\x8f\xe2\x13\xff\x2f\xe1\x03\xa0\x52\x40\xc2\x71\x05\xb4\x69\x46\x0b\x27\x01\xdf\x2d\x1c\x2f\x62\x69\x6e\x2f\x73\x68\x58";
int main(int argc, char **argv)
{
# Helps Visualizing overall summary of all features in a dataset
# !pip install numpy
# !pip install pandas
# !pip install autoviz
# !pip install xlrd
# !pip install xgboost
from autoviz.AutoViz_Class import AutoViz_Class
AV = AutoViz_Class()
# Modified from source: https://machinelearningmastery.com/feature-selection-machine-learning-python/
# Feature Selection with Univariate Statistical Tests
from pandas import read_csv
from numpy import set_printoptions
from sklearn.feature_selection import SelectKBest
from sklearn.feature_selection import f_classif
from sklearn.feature_selection import chi2
#!/usr/bin/env python
# -*-coding:utf-8 -*-
'''
@File : redaction.py
@Time : 2023/02/09 20:57:22
@Author : Shanto Roy
@Version : 1.0
@Contact : sroy10@uh.edu
@License : (C)Copyright 2020-2021, Shanto Roy
@Desc : Class that replace real information with fake believable ones.
Cloud Tool Local Alternative
Google Docs Microsoft Word
Google Slides Microsoft PowerPoint
Google Sheets Microsoft Excel
Trello Asana
Zoom Skype
Slack Microsoft Teams
GitHub Git
Canva Adobe Photoshop
#!/usr/bin/env python
# -*-coding:utf-8 -*-
'''
@File : custom_api.py
@Time : 2023/04/09 17:01:04
@Author : NSL
@Version : 1.0
@Contact : sroy10@uh.edu
@Desc : None
'''
#!/usr/bin/env python
# -*-coding:utf-8 -*-
'''
@File : splitwise_personal_cost_analytics.py
@Time : 2023/03/09 13:08:34
@Version : 1.0
@Contact : sroy10@uh.edu
@Desc : Splitwise Class for analyzing and visualizing personal expenditure
'''